| Summary: | 碩士 === 國立交通大學 === 控制工程系 === 84 === This paper presents the improved fuzzy logic models (FLM) to
simulate the thermally based microelectronic manufacturing
process: the silicon deposition process in a barrel chemical
vapor deposition (CVD) reactor. To identify a FLM for a
process, there are two major tasks: structure and
parameter identifications. In structure identification, the
genetic algorithm is used to search for the optimal structure
so that the predictive capability of the FLM is increased. In
parameter identification, the adaptive learning rate that is
based on the sum of square errors between given data and
output of the FLM is chosen to increase the convergent speed of
the parameters. Several mathematical functions and a CVD
process are used to demonstrate the efficiency and accuracy
of the improved FLM in comparison with the existing fuzzy
models.
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